Integral Logistics Management — Operations Management and Supply Chain Management Within and Across Companies

5.3.2 Overview of Materials Management Techniques — Kanban, Order Point Technique, Cumulative Production Figures Principle (CPFP).

Intended learning outcomes: Disclose the basic classification of detailed planning techniques in materials management. Produce an overview on techniques such as Kanban, order point technique, and CPFP (cumulative production figures principle).

Figures and distinguish among the common techniques of detailed planning techniques in materials management. First, Figure classifies planning techniques according to the characteristic features frequency of customer demand and unit cost of items (as defined in Figure

Fig.        Classification of detailed planning techniques in materials management.

Demand for low-cost items (with the exception of unique demand) or demand for high-cost items with a continuous or regular demand pattern is determined using stochastic techniques.

  • In general, forecasting techniques determine future demand analy­tically or intuitively. From this perspective, demand forecasting is a technique for determining stochastic independent demand and is thus part of stochastic materials management. Once demand has been forecasted, different stochastic planning techniques exist, all being relatively simple. They are described at a first glance below.
  • Dependent demand is calculated as if it were independent demand — that is, ignoring its possible derivation from independent demand.
  • For low-cost items, a very high service level has priority. This holds true especially in the event where the item appears on the bill of material with many components (see the case mentioned previously in Fig. Low stock inventory is, due to the low carrying cost involved, of secondary importance.
  • For high-cost items, short lead times in the flow of goods, meaning rapid value-adding and administrative processes, take priority, requiring simple data and control flow. Inventory is possible: the continuous or regular demand pattern guarantees a future demand (for end products: a customer order)[note 516] within a short time. However, because of the high unit cost, the inventories should be low, which generally requires small batch sizes.

Forecasting techniques will be discussed in Chapter 9. The planning techniques mentioned are explained in detail in different chapters. At a first glance, they are described in brief as follows.

  • Kanban is a simple technique for stochastic materials manage­ment, but it requires invested capital. Small buffer storages kept close to the user operation will contain a maximum number of standard containers or bins holding a fixed number of items. The Kanban card is a means to identify the contents of the container and to release the order. The order batch size will be one or more empty containers, which are either sent directly by work center employees to the supplier or collected by one of the supplier’s employees. The supplier executes the implied stock replenishment order and delivers it directly to the buffer. The Kanban feedback loop is then closed. One of the tasks of long- and medium-term planning is to determine the type and number of Kanban cards for each feedback loop. See Section 6.3.
  • The cumulative production figures principle (CPFP) is another simple technique. In the manufacturing process of a certain product, the technique in essence counts the number of intermediate products at particular count points. It compares this amount to the planned flow of goods, through putting the two cumulative production figure curves, or whole cumulative production figure diagrams — the projected diagram and the actual diagram — one on top of the other. The object is to bring the actual diagram closer to the projected diagram, which can be accomplished by speeding up or slowing down the manufacturing process. See Section 6.4.
  • The (stochastic) order point technique compares goods on hand — plus open orders and, sometimes, minus allocated quantities (reservations) — with a certain level called the order point. If the quantity calculated in this manner is no greater than the order point, the system generates orders to replenish stock. These replenishment orders can then be released. The order point is normally calculated as average usage (a forecast!) during the replenishment lead time plus safety stock, or reserved stock, to compensate for forecast errors. The “optimum” order quantity or batch size, called the economic order quantity (EOQ), can be determined through comparing ordering and setup costs to carrying cost. See here Chapter 11.

Continuation in next subsection (5.3.2b).

Course section 5.3: Subsections and their intended learning outcomes

  • 5.3.4b Overview of Scheduling and Capacity Management Techniques

    Intended learning outcomes: Produce an overview on order-oriented infinite loading, order-wise infinite and finite loading, operations-oriented and order-oriented finite loading, constraint-oriented finite loading, load-oriented order release (Loor), capacity-oriented materials management (Corma).

  • 5.3.5 Available-to-Promise (ATP) and Capable-to-Promise (CTP)

    Intended learning outcomes: Explain available-to-promise (ATP) and the determination of ATP quantities. Produce an overview on the techniques of multilevel available-to-promise (MLATP) and capable-to-promise (CTP).